Towards an OWL-based framework for extracting information from clinical texts

Authors:
Nate Blaylock;William de Beaumont;James Allen;Hyuckchul Jung
Affiliations:
Florida Institute for Human and Machine Cognition (IHMC), Pensacola, Florida;Florida Institute for Human and Machine Cognition (IHMC), Pensacola, Florida;Florida Institute for Human and Machine Cognition (IHMC), Pensacola, Florida;Florida Institute for Human and Machine Cognition (IHMC), Pensacola, Florida
Venue:
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Year:
2011

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Abstract

In this paper, we present our ongoing work towards an OWL-based framework for extracting a variety of information (including patient history) from clinical texts. Our framework integrates a well-known natural language processing (NLP) system by converting its ontology and output logical form interpretation into the Web Ontology Language (OWL). The OWL-based Semantic Query-Enhanced Web Rule Language (SQWRL) is then used as a platform for authoring Semantic Web-aware rules for extracting information of interest from the OWL knowledge based created from parsing a clinical report. We also describe our ongoing work on using this system for extracting a timeline-based patient medical record from the history of present illness section of clinical texts.